MATEC Web Conf.
Volume 216, 2018X International Scientific and Technical Conference “Polytransport Systems”
|Number of page(s)||6|
|Section||Construction and Transport Machinery, Non-Destructive Testing and Technical Diagnostics|
|Published online||17 October 2018|
Forecast model for estimating the service life of a diagnosed object based on the Neyman–Pearson method
Irkutsk State Transport University, 664074 Irkutsk, Russia
* Corresponding author: firstname.lastname@example.org
The paper is aimed at developing a forecast model for estimating the service life of a diagnosed object based on the Neyman–Pearson method. It presents a procedure for selecting necessary and sufficient number of diagnostic indicators using the forecast model. The technique has been tested on the basis of a power transformer with a liquid dielectric. A condition-based operation strategy has been proposed for the transformer. According to this strategy, the iron impurity content in the dielectric liquid (oil) of the transformer should be measured every year of operation. Based on the forecast model, it is possible to calculate the variation of average risk (R) and a threshold value of iron impurity content in the transformer oil (k0) for each year of operation. Using these parameters, a reliable forecast model can be constructed to estimate the remaining service life of the transformer. The obtained relationships make it possible to identify a scientifically grounded stage in the service life of a diagnosed object, at which the number of measurable diagnostic indicators (indicators that are necessary for assessing the real technical condition of equipment) can be minimized.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.